Rail Train Research Articles

The influence of forward leaning postures on passenger injury in urban rail train collision

The influence of forward leaning postures on passenger injury in urban rail train collision

Steering Mechanism and Capability of Forced Steering Device for Low-Floor Light Rail Train

For 70% low-floor trains on the light rail lines in Changchun, a multi-linkage forced steering device (FSD) is developed aiming at relieving the independently rotating wheelset (IRW) excessive flange wear and improving IRW bogie system running safety on curve line. This FSD employs guiding mode of steering four independently rotating wheels separately in a two-axle bogie, that is, four FSDs are employed to work together to realize the steering of a two-axle bogie. One side of an FSD is connected to the axle of an independently rotating wheel while the other side is attached to the front or rear vehicle body. When train passes through curve, the yaw angle between the IRW bogie and the front or rear carbody drives the linkage system to rotate to guide the independently rotating wheel towards its radial position. The coupled vehicle-track dynamics model for a 6-module single-type low-floor light rail train is developed and simulations of the train passing through tangent and curved tracks with and without FSD proposed are carried out. The results indicate that the FSD can improve the IRW restoring capability on tangent track and curve negotiation performance on whether sharp, medium, or large curved track. For example, passing through a curve with a radius of 200[Formula: see text]m, the IRW friction work has the biggest drop by 62.07% and the wheelset attack angle is second with a reduction rate of 55.02%. Adopting of larger steering stiffness, smaller steering clearance, and lever ratio greater than the ideal value can guarantee the higher steering ability of FSD. Besides, lower longitudinal stiffness of the trailer primary suspension is recommended because it can also enhance the steering ability of the FSD.

Research on Multi-Objective Optimization Methods of Urban Rail Train Automatic Driving Based on NSGA-II

In order to improve the control performance of automatic train operation (ATO) in urban rail trains, five typical operating sequences of urban rail trains were studied. Under the condition of meeting the safety and comfort principles of train operation, a train dynamics model was established to achieve the goals of low energy consumption, short running time, and high stopping accuracy in urban rail transit trains. In the process of finding a multi-objective solution to this problem, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) was used with an elite retention strategy, and the optimal Pareto multi-objective solution set was sought. In the process of optimal solution weight assignment, the hierarchical analysis Mahalanobis distance method, which combines subjective and objective analysis, was used. Finally, taking the Beijing Yizhuang subway line as the background design example, the simulation verified the effectiveness and feasibility of the algorithm and obtained high-quality automatic train driving curves under various working conditions. This research has important reference significance for the actual operation of automatic driving in urban rail trains.

An Efficient Time‐Sensitive Networking Traffic Scheduling Method for Train Communication Network

As a critical system of rail train, the train communication network (TCN) is an integrated central platform that is used to realize the train operation control, condition monitoring, and data transmission. With the development of train intelligence, the scale of data flow in TCN continues to expand, and the control data and monitoring data must be real‐time transmitted to ensure the safe and reliable operation of the train. Time‐sensitive network (TSN) can be applied as the next‐generation TCN solution, which provides end‐to‐end data transmission with extremely low delay and high reliability based on Ethernet. For the application of TSN technology in TCN, a single frame simple scheduling method is proposed to effectively reduce the worst end‐to‐end delay of the entire network, which improve the real‐time performance of TSN‐based TCN. The network topology and data flow characteristics in TCN are analyzed, a series of scheduling constraints are constructed, and the satisfiability modulo theories (SMT) is used to obtain a gate control list (GCL) to ensure the real‐time performance of time‐trigger streams. Finally, the TCN simulation model is established using OMnet++ software, the experiment results show that the proposed method can effectively reduce the overall delay and jitter, and meet the real‐time requirement of TCN. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Dynamic behavior of beam with an elastic foundation under the extended moving load for electromagnetic launch rail-structure

The distributed load with loaded area being extended over the whole structure (i.e., the extended moving load) that occurs during the operation of an electromagnetic launch rail-structure, is different from loading cases studied previously such as the concentrated load or distributed load on a finite segment (i.e., the single moving load), or a series of single moving loads in a periodic pattern (i.e., the periodic moving load). In this paper, a nonlinear finite element model is proposed by modeling the rail-structure as a Euler-Bernoulli based beam on an elastic foundation to study the dynamics of rail-beam under such an extended moving load. The proposed model is firstly verified by comparison with the analytical solution for the rail-vibration response under the extended moving load at constant speed, and the model feasibility is further revealed by comparison with the experimental results of rail strain. The significant differences of rail vibration modes are observed between the extended moving load and the single, or periodic moving load. Moreover, the maximum error of the middle of the rail between the linear forcing and nonlinear forcing will decrease with the increase in the foundation elastic modulus, but increases with the increase in the pulse current. Those results will improve our understanding on dynamics of beam under the more comprehensive loading cases.

Train Trajectory-Following Control Method Using Virtual Sensors.

Trajectory-following control is the basis for the practical application of an articulated virtual rail train transportation system. In this paper, a planar nonlinear dynamics model of an articulated vehicle is derived using the Euler-Lagrange method. A trajectory-following control strategy based on the first following point is proposed, and a feedback linearization control algorithm is designed based on the vehicle dynamics model to achieve the trajectory following of the rear vehicle. Based on the target trajectory formed by the first following point and measured by virtual sensors, a vector analysis method grounded in geometric relationships is proposed to solve in real time for the desired position, velocity, and acceleration of the vehicle. Finally, a MATLAB/SIMPACK dynamics virtual prototype is established to test the vehicle's trajectory-following effectiveness and dynamics performance under lane change and circular curve routes. The results indicate that the control algorithm can achieve trajectory following while maintaining good vehicle dynamics performance. It is robust to variations in vehicle mass, vehicle speed, tire cornering stiffness, and road friction coefficient.

Design and experimental study of copper bars for high voltage equipment boxes of rail trains

Abstract This article describes the theoretical design and selection of copper bars, simulation of electric field theory for different structural copper bars, and vibration anti loosening tests for different fasteners, providing theoretical and data support for the forward design of high-voltage copper bars, and providing certain guidance for subsequent projects. The design and selection of copper bars have been verified to meet the requirements through vibration tests and impulse withstand voltage tests.

LiDAR-Based Urban Three-Dimensional Rail Area Extraction for Improved Train Collision Warnings.

The intrusion of objects into track areas is a significant issue affecting the safety of urban rail transit systems. In recent years, obstacle detection technology based on LiDAR has been developed to identify potential issues, in which accurately extracting the track area is critical for segmentation and collision avoidance. However, because of the sparsity limitations inherent in LiDAR data, existing methods can only segment track regions over short distances, which are often insufficient given the speed and braking distance of urban rail trains. As such, a new approach is developed in this study to indirectly extract track areas by detecting references parallel to the rails (e.g., tunnel walls, protective walls, and sound barriers). Reference point selection and curve fitting are then applied to generate a reference curve on either side of the track. A centerline is then extrapolated from the two curves and expanded to produce a 2D track area with the given size specifications. Finally, the 3D track area is acquired by detecting the ground and removing points that are either too high or too low. The proposed technique was evaluated using a variety of scenes, including tunnels, elevated sections, and level urban rail transit lines. The results showed this method could successfully extract track regions from LiDAR data over significantly longer distances than conventional algorithms.

Comparison of train noise and vibration measurements with U.S. Department of Transportation model predictions

Wayside noise and ground-borne vibration measurements of freight and light rail train operations were carried out in Denver, CO in support of the Burnham Yard Transportation Planning Study being pursued by the Colorado Department of Transportation (CDOT). This study was intended to evaluate various track layout alternatives for the Consolidated Main Line (CML) freight railroad alignment and enhancement of Regional Transportation District (RTD) light rail operations while maintaining options for Front Range Passenger Rail (FRPR) within Burnham Yard and the surrounding areas. The objective of the measurements was to compare measured train noise and vibration levels with predictions using models sanctioned by the U.S. Department of Transportation (USDOT) in order to validate the use of these models to assess the noise and vibration impacts of the project alternatives. The models included the Federal Railroad Administration (FRA) Chicago Rail Efficiency And Transportation Efficiency (CREATE) freight noise model, the FRA Horn Noise Model, and the models included in the Federal Transit Administration (FTA) Transit Noise and Vibration Impact Assessment Manual. Based on a comparison of measured and modeled results, it was concluded that the USDOT models could be used to assess noise and vibration from train operations in the Burnham Yard Study Area.

All-Wheel Steering Tracking Control Method for Virtual Rail Trains with Only Interoceptive Sensors

A virtual rail train (VRT) is a multi-articulated vehicle as well as a novel public transportation system due to its low economic cost, environmental friendliness and high transit capacity. Equipped with all-wheel steering (AWS) and a tracking control method, the super long VRT can travel on urban roads easily. This paper proposed a tracking control approach using only interoceptive sensors with high scene adaptivity. The kinematic model was established first under reasonable assumptions when the sensor configuration was completed simultaneously. A hierarchical controller consists of a front axle controller and a rear axle controller. The former applies virtual axles theory to avoid motion interference. The latter generates a first-axle reference path with path segmentation and a data updating method to improve storage and computational efficiency. Then, a fast curvature matching rear axles control method is developed with an actuator time delay considered. Finally, the proposed approach is verified in a hardware in loop (HIL) simulation under various situations with predefined evaluation standards, which shows better tracking performance and applicability.

Coordinated Control of the Onboard and Wayside Energy Storage System of an Urban Rail Train Based on Rule Mining

There are three major challenges to the broad implementation of energy storage systems (ESSs) in urban rail transit: maximizing the absorption of regenerative braking power, enabling online global optimal control, and ensuring algorithm portability. To address these problems, a coordinated control framework between onboard and wayside ESSs is proposed in this study, and the related control strategy is obtained by transforming the global optimization problem into a combination of rule-based and local optimization problems. The design process of the strategy is divided into three parts: offline optimization, rule extraction, and local optimization. First, a genetic algorithm is used to optimize the charge/discharge threshold curves under typical operational conditions. Then, the rules of offline optimization results are obtained from an expert system, and the nonlinear rules are mined with local optimization methods. Finally, a coordinated strategy is presented based on the outcomes of the three parts. A power hardware-in-the-loop (PHIL) experimental platform based on RTLAB is built, and the above coordination strategy is verified based on data for the Beijing Metro Batong Line. The experimental results show that the strategy can effectively improve the energy-saving rate and reduce the regeneration failure rate substantially, with the effect being close to the offline global optimal solution. The algorithm proposed in this paper achieves near global optimal energy-saving optimization results with lower computational costs, and has strong portability, providing a good solution for the large-scale application of onboard and wayside energy storage coordination control.

A rolling bearing fault diagnosis method based on interactive generative feature space oversampling-based autoencoder under imbalanced data

With the rapid development of railroads and the yearly increase in the scale of operation, the safe operation and maintenance of rail trains have become particularly important. Among them, deep learning-based bearing fault diagnosis methods have attracted more and more attention in rail train operation and maintenance. However, rail trains usually operate normally. Collecting complete fault data for deep learning model training is often difficult. Such scenarios with a large difference between the number of normal data and fault data usually affect the performance of fault diagnosis models. Here, an interactive generative feature space oversampling-based autoencoder (IGFSO-AE) is proposed to realize fault sample generation under imbalanced data. First, the original vibration signal is converted into a semantically stable amplitude–frequency signal by fast Fourier transform and input into the autoencoder; second, the order of the hidden layer space features of the autoencoder is randomly exchanged, and the interactive sample generation learning strategy trains the autoencoder; then, interpolation oversampling is used to interpolate samples in the hidden layer space where the Euclidean distance between samples is large, and is input into the decoder, the generated samples are mixed with the original samples to form a new training set, which is used to train the intelligent fault diagnosis model and output the diagnosis results. Finally, the performance of the proposed method is evaluated using the publicly available bearing dataset and the bogie-bearing fault simulation bench in our lab. The experimental results show that IGFSO-AE can generate diverse samples with incremental information and exhibits robustness and superiority in different imbalanced proportions of data.

A TLOT train gearbox fault diagnosis method based on ridge extraction under variable speed conditions

Owing to the rapidly varying working conditions of urban rail trains, the rotational speed conditions constantly shift in a short time span. As a key component of the running gear, the gearbox generates non-stationary vibration signals, making it challenging to monitor its health status. To address this challenge, a tacholess order tracking method (TLOT) based on ridge extraction method is proposed in this paper. This method determines the optimal search starting point using the time-frequency Gini coefficient and extracts the time-varying gearbox meshing frequency components from the time-frequency representation results. Furthermore, the TLOT method is utilized to process the strongly time-varying gearbox signal. In the order domain, multiple frequency components are extracted to reconstruct the signal. Simulation and experimental results demonstrate that the proposed method achieves a superior ridge extraction effect on gearbox experimental signals. It accurately converts unstable signals into angular domain stable signals, enhancing the energy aggregation of time-varying unstable signals in the order domain. This approach addresses the problem of weak harmonic component extraction from gearbox signals and effectively reduces interference in the resonance band, realizing fault diagnosis of the gearbox under unstable working conditions.

Building brand equity as a dynamic capability during Gautrain public–private partnership patronage guarantee controversy

Learning outcomes After completion of the case study, the students will be able to gain knowledge on public–private partnerships (PPPs) in emerging markets; understand how to apply the sensing element of the dynamic capabilities framework in analysing context, especially in emerging market context; and understand how to apply the dynamic capabilities framework to the process of developing brand equity. Case overview/synopsis On 20 March 2020, in Johannesburg South Africa, Dr Barbara Jensen Vorster, the head of corporate communications and marketing at the Gautrain Management Agency, was considering her dilemma of how to manage stakeholders at a time when the patronage guarantee was under question. The nature of the Gautrain PPP transport contract entailed a revenue guarantee that was called a patronage guarantee. How did they build their Gautrain brand equity during the Gautrain PPP patronage guarantee controversy? This case study highlights the perspectives of multiple stakeholders which places the Gautrain brand equity under strain. The Gautrain brand identity was created to project an integrated, overarching brand position for the construction project and later the operating company. The logo illustrated Africanisation, and the slogan “For People on the Move” represented a modern collaborative approach. Upholding the status of the brand is an important quest for the corporate communications and marketing team, and therefore the issue around the patronage guarantee must be addressed. This case study illustrates contrasting views about the Gautrain being elitist versus the rapid rail train enabling economic prosperity. The pro-prosperity versus pro-economic development values were at the heart of the different opinions around the patronage guarantee. Students are therefore confronted with their own values while the case study aims to drive an awareness or consciousness around these issues in an emerging market. Complexity academic level This case study is appropriate for advanced undergraduate and Master of Business Administration courses focused on marketing, communications and/or stakeholder management, such as in business and society courses. At both levels, the case study will be valuable in generating discussion on communications models and how to manage stakeholders ranging from government to community representatives. In courses where dynamic capabilities theory is taught, this case study will offer a specific application of this model in the context of brand communications and building brand equity in times of controversy. Supplementary materials Teaching notes are available for educators only. Subject code CSS 3: Entrepreneurship.

Energy management strategy of urban rail hybrid energy storage system based on fuzzy logic system

Energy management is an important link in the effective functioning of hybrid energy storage systems (HESS) within urban rail trains. This factor significantly impacts the operational stability and economic efficiency of urban rail systems. Safety issues arise from DC bus voltage fluctuations due to varying train conditions. To address these issues, this paper proposes an energy management strategy for the urban rail HESS, which builds upon a traditional double closed-loop control strategy. This strategy incorporates a fuzzy logic system to regulate power distribution parameters and discharge thresholds dynamically. Real-time monitoring of the state of charge (SOC) of the energy storage device informs the decision-making process, utilizing a fuzzy inference system to effectively regulate power and energy distribution in response to the distinct characteristics of batteries and super-capacitors. This approach aims to mitigate power fluctuations within the traction network. To validate the effectiveness of the proposed energy management strategy, the study conducts a comprehensive simulation experiment using MATLAB/Simulink. The simulation results confirm the efficacy of the proposed strategy, highlighting its potential to enhance the stability and overall performance of urban rail train operations.

Dynamics Response of Rail Vehicle Induced by Incorporating Electric-Dominated Transmission Component

Abstract As an important component of train speed regulation, traction transmission system is the power source and the main transmission component of traction force. Its dynamic characteristics can affect the dynamic performance of vehicle system to a certain extent. With the rapid development of rail train transportation in China, the running speed of the train continues to improve, the dynamic characteristics of the vehicle is becoming more complex, and the influence of the electrical part of the traction transmission system gradually appears. The motor and gearbox are crucial components of the train power bogie to complete the conversion and transmission of electric energy to mechanical energy, with their dynamic characteristics are most directly affected by the electrical characteristics of the traction system. In this work, a vehicle electro-mechanical coupling mathematical model based on multi-body dynamics was established by explicitly incorporating the electric-induced traction into the transmission system, to study the influence of traction system vibration on vehicle dynamics. The dynamics responses of the lateral and longitudinal vibration on vehicle motor and gearbox were quantitatively analysed from the traction drive system. Compared with the line test, it was observed that 12-times of the fundamental frequency of the rotor has a great influence on the motor and gearbox.

Working with Giants: A Brief Overview of the University of Southern California Sea Grant’s Work with the Ninth Largest Port Complex in the World

Three-quarters of US trade and 90% of international trade are still moved by ships, and the global demand for waterborne trade is expected to more than double by 2025 (USCG, 2018). The adjacent Ports of Los Angeles and Long Beach constitute the largest port complex in the United States, the ninth largest in the world, handling over $500 billion US dollars in cargo and nearly 19 million shipping containers annually (POLA, 2023; POLB, 2023). What may seem like chaos at first glance is actually a highly choreographed dance. A network of one million regional jobs and close to four million national jobs support this interconnected system of football-field-sized container ships, oil tankers, carriers with thousands of imported cars, over one hundred sky-scraping cranes, thousands of trucks, and hundreds of miles of train rails. (POLA and POLB, 2020; POLA, 2023; POLB, 2023). In this dance, speed is time, and time is money. However, being bigger and faster comes at a cost—burning more diesel fuel, generating more greenhouse gas emissions, and threatening several species of endangered whales.

Investigation and Analysis of Electromagnetic Interference for PWM Encoder of Urban Rail Train

Electromagnetic compatibility (EMC) is an important factor in ensuring the safe operation of the sensitive electronic equipment on urban rail trains. The pulse width modulation (PWM) encoder of an urban rail train exported from China to Brazil is sometimes affected by electromagnetic interference (EMI), which causes the train to fail to run properly. To solve this problem, the EMC test is performed on the PWM encoder to identify the coupling path and the type of interference source. The EMI coupling model and the vehicle-catenary-rail model are established by using an electromagnetic transients program (EMTP) to analyze the mechanism of interference coupling. It is shown that the unbalanced voltage of the train body caused by the backflow of the grounding current is the root cause of the interference of the PWM encoder. The maximum voltage coupled to the internal port of the PWM encoder is about 1894 V, which is sufficient to burn out the encoder. A measure to suppress the interference by installing thyristor surge suppressors (TSS) P0300SC is proposed, which effectively solves the EMI problem of the PWM encoder.

Modelling the pedestrian’s willingness to walk on the subway platform: A novel approach to analyze in-vehicle crowd congestion

A common behavior pattern observed on subway platforms is that pedestrians walk downstairs from the escalator and choose a door to wait for a rail train. Interestingly, pedestrians often walk to farther doors rather than the nearest one to the escalator. This paper proposes a new concept, called willingness to walk (WTW), to describe pedestrians' behavioral characteristics, including their psychological tendency to stay in their original queue or to walk to farther queues. Two regression models are proposed to quantitatively measure WTW, both of which are calibrated using an inequality-based least square method. Observation data are collected through field investigation and simulation software. The calibration results confirm the existence of WTW. The proposed method is then applied to analyze the distribution of waiting passengers on the platform and the level of in-vehicle crowding. Simulation results demonstrate that the proposed WTW models can reliably approximate the actual passenger load in carriages.

A holistic solution to virtual coupling based urban rail train control system

Virtual coupling (VC) is an emerging concept that is gaining popularity in railway control systems. It has the potential to significantly enhance railway capacity and flexibility, and has attracted considerable research attention. This study explores several key aspects of VC research in the context of urban rail transit systems, including system structure, train platoon control method, scenario definition, and train scheduling. The paper presents three main contributions: Firstly, it proposes a potential system structure for VC and discusses infrastructure occupancy procedures within typical operational scenarios. Secondly, a VC platoon controller based on the adaptive back-stepping method is designed to realize the function of the operation layer. Thirdly, combining operational scenario definition and control methods, we propose a VC train scheduling method based on mixed integer linear programming (MILP). A case study demonstrated that the proposed solution could effectively achieve the primary functions of VC.